Design of OpenCL framework for embedded multi-core processors
| Autor: | Youngho Ahn, Ki-Seok Chung, Byung-Jin Kim, Jung-Hyun Hong |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Multi-core processor
Application programming interface business.industry Computer science Software development Symmetric multiprocessor system Thread (computing) ComputerSystemsOrganization_PROCESSORARCHITECTURES computer.software_genre Media Technology Key (cryptography) Operating system Hardware acceleration Electrical and Electronic Engineering business Execution model computer Host (network) |
| Zdroj: | IEEE Transactions on Consumer Electronics. 60:233-241 |
| ISSN: | 0098-3063 |
| Popis: | In modern mobile embedded systems, various energy-efficient hardware acceleration units are employed in addition to a multi-core CPU. To fully utilize the computational power in such heterogeneous systems, Open Computing Language (OpenCL) has been proposed. A key benefit of OpenCL is that it works on various computing platforms. However, most vendors offer OpenCL software development kits (SDKs) that support their own computing platforms. The study of the OpenCL framework for embedded multi-core CPUs is in a rudimentary stage. In this paper, an OpenCL framework for embedded multi-core CPUs that dynamically redistributes the time-varying workload to CPU cores in real time is proposed. A compilation environment for both host programs and OpenCL kernel programs was developed and OpenCL libraries were implemented. A performance evaluation was carried out with respect to various definitions of the device architecture and the execution model. When running on embedded multi-core CPUs, applications parallelized by OpenCL C showed much better performance than the applications written in C without parallelization. Furthermore, since programmers are capable of managing hardware resources and threads using OpenCL application programming interfaces (APIs) automatically, highly efficient computing both in terms of the performance and energy consumption on a heterogeneous computing platform can be easily achieved. |
| Databáze: | OpenAIRE |
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